Abstract
An algorithm for automated QT interval assessments has been developed and evaluated using the PhysioNet QT database and the electrocardiogram multilead database (2 collections of electrocardiograms with different characteristics, eg, numbers of leads and expert annotations). QRS onset and coarse T offset detection was based on the definition of a short time window, within which the range of signal amplitudes was calculated and compared to given threshold values. The final position of T offset was based on a combination of 3 methods: decreasing thresholds, multiple tangents, and a model based approach. The evaluation was based on the comparison of a waveform marker as computed automatically, and those of the human experts. Mean and standard deviation of those differences compared well to other algorithms and to inter-expert variations. Waveform marker detection was successful in at least 98% of the annotated beats in both databases, thus, indicating the robustness of the proposed method.
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